Bennett Wilburn

Research Interests: I'm a system designer who currently thinks
computer graphics and vision are pretty cool. In the short term, I'd
like to keep working in this space. I've gotten a lot of mileage from
building a custom system for these applications (see below), and in
the future, I'd like to hunt down other application domains that could
benefit from a combined hardware/software approach.

The Stanford
Multiple Camera Array. My research focus at Stanford is high
performance imaging using cheap image sensors. To explore the
possibilities of inexpensive sensing, I designed the Stanford Multiple
Camera Array, shown at left. The system uses MPEG video compression
and IEEE1394 communication to capture minutes of video from over 100
CMOS image sensors using just four PC's. The array has been
operational since February 2003, and since then we've developed our
geometric and radiometric calibration pipelines and explored several
applications.

Publications:

Surface Enhancement Using Real-Time Photometric Stereo and Reflectance Transformation.
Proc. Eurographics Symposium on
Rendering 2006. Photometric stereo recovers per-pixel estimates
of surface orientation from images of a surface under varying lighting
conditions. Transforming reflectance based on recovered normal
directions is useful for enhancing the appearance of subtle surface
detail. We present the first system that achieves real-time
photometric stereo and reflectance transformation. We also introduce
new GPU-accelerated normal transformations that amplify shape
detail. Our system allows users in fields such as forensics,
archaeology and dermatology to investigate objects and surfaces by
simply holding them in front of the camera. See this video for a summary of
the work and a demonstration of the system.

Synthetic Aperture Focusing Using a Shear-Warp Factorization of the Viewing Transform. Vaibhav Vaish, Gaurav Garg, Eino-Ville Talvala, Emilio Antunez, Bennnett Wilburn, Mark Horowitz, and Marc Levoy.
Proc. Workshop on Advanced 3D
Imaging for Safety and Security (in conjunction with CVPR 2005) Oral
presentation. 2005). This paper analyzes the warps required
for synthetic aperture photography using tilted focal planes and
arbitrary camera configurations. We characterize the warps using a new
rank-1 contraint that lets us focus on any plane, without having to
perform metric calibration of the cameras. We show the advantages of
this method with a real-time implementation using 30 cameras from the
Stanford Multiple Camera Array. This video
shows our results.

High
Speed Video Using A Dense Camera Array. Bennett Wilburn, Neel
Joshi, Vaibhav Vaish, Marc Levoy and Mark Horowitz. Presented at CVPR 2004. We create a
1560fps video camera using 52 cameras from our array. Because we
compress data in parallel at each camera, our system can stream
indefinitely at this frame rate, eliminating the need for
triggers. Here's the video
of the popping balloon shown at left. The web page for the paper has
several more videos.

Using
Plane + Parallax for Calibrating Dense Camera Arrays. Vaibhav
Vaish, Bennett Wilburn and Marc Levoy. Presented at CVPR 2004. We present a method for plane
+ parallax calibration of planar camera arrays. This type of
calibration is useful for light field
rendering and synthetic aperture photography and is simpler and
more robust than full geometric calibration. Synthetic aperture
photography uses many cameras to simulate a single large aperture
camera with a very shallow depth of field. By digitally focussing
beyond partially occluding foreground objects like foliage, we can
blur them away to reveal objects in the background. Here's an example
Quicktime
video.

Hardware-accelerated
dynamic light field rendering. Bastien Goldlucke, Marcus Magnor,
Bennett Wilburn. Vision, Modelling
and Visualization 2002. Marcus and I started a collaboration
while he was a post-doc at Stanford to render novel views from
positions between the 6 cameras in our light field camera
prototype. His student Bastien continued this work, adding new
disparity estimation methods and hardware acceleration for the image
warps.

Spatiotemporal
Sampling and Interpolation for Dense Camera Arrays. This is a work
in progress. We have already shown that we can simulate a high-speed
camera by tightly packing many cameras with staggered trigger
times. If we spread the cameras out, we can capture views from
multiple positions and multiple times for spatiotemporal view
interpolation--synthesizing new views from positions and times not in
our captured set of images. Our improved temporal resolution lets us
use simpler, image-based methods to generate new views. We can also
eliminate the alignment errors in the high-speed video work
above. Here's an example video.